This Specialization equips learners with the skills to design, implement, and deploy machine learning solutions using Java. Starting with core ML concepts like regression, classification, and clustering, learners will apply Java-based tools such as Weka, Smile, Tribuo, and Deeplearning4j to build real-world models. The courses cover data preprocessing, model training, evaluation, deep learning, NLP, and large-scale ML with Spark and Mahout. Learners will also explore advanced topics like federated learning and MLOps practices using Jenkins and GitHub Actions. By the end of the specialization, participants will be able to create and deploy scalable ML applications in enterprise environments with Java.
Applied Learning Project
Learners will design and implement end-to-end machine learning solutions using Java libraries such as Weka, Tribuo, and DL4J. They will analyze real-world problems like fraud detection and equipment failure, and deploy models through Spring Boot APIs using industry-relevant workflows.
